feature-extraction

Describe the issue:
During computing Channel Dependencies reshape_break_channel_dependency does following code to ensure that the number of input channels equals the number of output channels:

in_shape = op_node.auxiliary['in_shape']
out_shape = op_node.auxiliary['out_shape']
in_channel = in_shape[1]
out_channel = out_shape[1]
return in_channel != out_channel

This is correct

Love the book! Ran into this display issue when viewing it on Chrome's PDF viewer:

https://github.com/4paradigm/OpenMLDB/blob/230f99b9b5744f2663b0253a87a2496c9f5ce96b/java/openmldb-taskmanager/src/main/scala/com/_4paradigm/openmldb/taskmanager/JobInfoManager.scala#L141-L170

pstmt is useless, delete it. And delete statement in finally block.

Is your feature request related to a problem? Please describe.
Using the CLI to output parameters, those audio features who are multidimensional like amplitudeSpectrumand mfcc will not get corresponding label names in the first row of the generated csv-file. This makes it complicated to import using csv-importers like pandas in Python.
It's also unclear which bin each column represents.

Add missing_only functionality to all imputers to use in combination with variables=None

When variables is None, the imputers select all numerical, or categorical or all variables by default. With the missing_only, it would select only those from each subgroup that show missing data during fit.

• I'm submitting a ...
  [/] enhancement

• Summary
  As a result of upgrading the Tensorflow version to 0.15.1, we should refactor all the dataSycn with arraySync. This will greatly improve the overall readability of the code.

Is there an existing issue for this?

• I have searched the existing issues.

Is your feature request related to a problem? Please describe.

Make Api for any object detection pipeline " towhee/img_object_embedding"

Describe the solution you'd like.

An api which return the output similar to the https://towhee.io/towhee/img_object_embedding

Describe an alternate solution.

_N